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Findings of the project on measuring Life Expectancy by socio-economic status group

Findings of the project on measuring Life Expectancy by socio-economic status group. Veronica Corsini European Commission, Eurostat - Population. Content. Background of the project Methodological issues Eurostat proposal and its developments Some results Next steps.

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Findings of the project on measuring Life Expectancy by socio-economic status group

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  1. Findings of the project on measuring Life Expectancy by socio-economic status group Veronica Corsini European Commission, Eurostat - Population Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  2. Content • Background of the project • Methodological issues • Eurostat proposal and its developments • Some results • Next steps Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  3. Background of the project • In 2007, Eurostat was requested to develop comparable information on mortality by socio-economic status group (SEG) on a regular basis for all EU Member States. • Proposal prepared by Eurostat and discussed with the countries in June 2009. • Technical Task Force set up in summer 2009 to tackle and resolve methodological and practical issues linked to the regular production and dissemination of such indicator. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  4. Methodological issues • Choice of SEG characteristic. • Choice of mortality indicator. • Cross-sectional/unlinked vs. prospective/record linked studies. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  5. Choice of SEG characteristic • Possible choices: educational attainment, occupational status, income (economic status or wealth). • Decision: use educational attainment as proxy for socio-economic group. • Advantages vs. disadvantages. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  6. Choice of mortality indicator • Several choices: death rates, life expectancy and life table based information, potential years of life lost, premature mortality, etc.. • Decision: life expectancy. • Life expectancy by educational attainment is considered a very important indicator of socio-economic inequalities in health. • Calculations done by Eurostat for all available countries. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  7. Cross-sectional vs. record linked studies • Cross-sectional studies: the distribution of deaths and population by SEG is identified via two different data sources. Problem: numerator-denominator bias  distortion of mortality indicators for some SEGs. Example: overestimation of mortality differentials by education. But: cheaper and more readily available. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  8. Cross-sectional vs. record linked studies • Record linked studies: linkage of death certificates with census information or population registers  same source is used to obtain the SEG. Choice of matching variables: unique identifier, deterministic linkage, probabilistic linkage. Longer to implement, more resources are needed but results are not affected by numerator-denominator bias. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  9. Eurostat proposal • Short term approach: use death and population series from the annual demographic questionnaire. Educational attainment is collected since reference year 2007 using ISCED97 broad groups: ISCED0_2, ISCED3_4, ISCED5_6: - deaths by sex, age and educational attainment: BG,CZ,DK,EE,IT,HU,MT,PL,PT,RO,SI,FI,SE;NO,ME,HR,MK,BA,RS,XK. - population by sex, age and educational attainment: DK,MT,FI,SE;NO. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  10. Eurostat proposal • Short term approach: Alternative for population: Labour Force Survey data: use the % shares of the population (5 years age groups) by ISCED97 groups in the LFS to break down the total population from the demographic data collection. But: LFS covers ages 15-74 and only private households. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  11. Eurostat proposal Example: Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  12. Eurostat proposal • Medium term approach: linkage of death certificates with census information from the 2011 censuses, broken down by educational attainment. The aim is to achieve a complete coverage of the countries but longer implementation time is needed. 2009 2010 2011 2012 2014 DK,MT,FI,SE,NO; BG,CZ,EE,IT,HU, PL,PT,RO,SI; HR,MK CENSUS DATA -> INDICATORS Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  13. Some examples Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  14. Task Force • Treatment of « unknown » and « not applicable » ISCED97 categories in deaths and population. • Use of LFS data. • Closing the life table. • Guidelines on census linkage. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  15. 1. Treatment of « unknown » and « not applicable » ISCED97 categories 3 possible choices: • they are ignored; • they are included into category ISCED0_2; • they are redistributed into categories ISCED0_2, ISCED3_4, ISCED5_6 proportionally to their relative sizes by sex and age.  sensitivity analysis  Redistribute proportionally the unknown among the three « known » categories. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  16. 2. Use of LFS data • Is it possible to refine the calculations? • What alternatives? • IIASA/VID database on educational attainment by age and sex for 120 countries, 1970-2050; • EU-SILC sample. • Decision: use LFS as above, but ….. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  17. 2. Use of LFS data ….. biases are to be expected ….. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  18. 3. Closing the life table • 85+ • Relevant age range is considered to be from 21 up to 74. • (ISCED97) mortality rates up to age 20 and from 75 to 85+ are assumed to be equal to those of the total population. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  19. 4. Guidelines on census linkage Statistics Austria has prepared a list of guidelines and related methodological issues: • linkage procedure and software, • handling of non-matched deaths, • actual calculation of death rates, • follow-up period, • possible sources of bias (closed population, deaths abroad, missing data, educational mobility, etc.). The guidelines have been presented to the countries in May 2010. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  20. 4. Guidelines on census linkage Information of June 2010: • Some NSIs are planning to carry out the census linkage exercise. • Some NSIs are already linking different sources to obtain the needed information. • Some NSIs will not carry out the exercise. • Some NSIs are not sure or have not decided yet. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  21. Some results 2007-2010 • Calculations done for DK, MT, FI, SE, NO using both deaths and population series by ISCED97 from the demographic data collection. • Calculations done for BG, CZ, EE, IT, HU, PL, PT, RO, SI, HR, MK using LFS information on educational attainment percentages. • Results are experimental statistics and will be developed further in the future, so any conclusions should be drawn with caution. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  22. Life expectancy gaps between high and low educational attainment 2010 - 1 Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  23. Life expectancy gaps between high and low educational attainment 2010 - 2 Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  24. Life expectancy by educational attainment 2010 - 1 Years Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  25. Life expectancy by educational attainment 2010 - 2 Years Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  26. Life expectancy gaps between men and women 2010 Years Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  27. To summarise ….. • An inverse relationship between educational attainment and mortality can be observed: at any age, life expectancy is shorter among persons with the lowest educational attainment and life expectancy increases with educational level. • Large differences in life expectancy by educational attainment can be observed among the Member States, particularly for men. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  28. To summarise ….. • Life expectancy for women at a given educational attainment is consistently higher than for men but there are smaller differences between educational attainment groups for women than for men. • However, based on the available data, social gaps between high and low levels have increased between 2007 and 2010 at age 30 for 40% of the countries for men and for 80% for women. • Women present another important ‘mortality advantage’ over men: life expectancy of men with higher education is generally lower than the life expectancy of women with the lowest educational attainment. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  29. Eurostat on line database http://epp.eurostat.ec.europa.eu/ Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  30. Next steps • «Regular» production of the indicator. • Follow up on census linkage if needed. • Wait for results from linkage exercise…. Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

  31. Thank you! Contact information: Veronica Corsini Eurostat, Unit F2 – Population veronica.corsini@ec.europa.eu Estimating social inequalities in Healthy Life Expectancy: challanges and opportunities, Bruxelles, 10/02/2012

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